Title :
Examination of the fuzzy subsethood theorem for data fusion
Author :
Buede, Dennis M.
Author_Institution :
Dept. of Syst. Eng., George Mason Univ., Fairfax, VA, USA
Abstract :
There continues to be substantial disagreement about which of the several methods to use in measuring and updating uncertainty in data fusion applications. In this paper we examine two popular methods, fuzzy sets and probability theory. Probability theory has been the traditional method for data fusion applications. Fuzzy sets have grown in popularity in Japan and Europe, with many successful control applications. Here we give a simple overview of fuzzy sets and then describe the fuzzy subsethood theorem as the best fuzzy approach for data fusion. Finally we compare the subsethood theorem to Bayes theorem for data fusion applications
Keywords :
fuzzy set theory; sensor fusion; uncertainty handling; Bayes theorem; data fusion; fuzzy measures; fuzzy set theory; fuzzy subsethood theorem; probability; target identification; Communication system control; Control systems; Equations; Europe; Fuzzy sets; Intelligent control; Intelligent systems; Measurement uncertainty; Set theory; Systems engineering and theory;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1994. IEEE International Conference on MFI '94.
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7803-2072-7
DOI :
10.1109/MFI.1994.398422
